Negotiation in distributed artificial intelligence: drawing from human experience

Author

Kersten, Gregory E. ; Szpakowicz, Stan

Author_Institution

Sch. of Bus., Carleton Univ., Ottawa, Ont., Canada

Volume

4

fYear

1994

fDate

4-7 Jan. 1994

Firstpage

258

Lastpage

270

Abstract

Distributed artificial intelligence and cooperative problem solving deal with agents who allocate resources, make joint decisions and develop plans. Negotiation may be important for interacting agents who make sequential decisions. We discuss the use of negotiation in conflict resolution in distributed AI and select those elements of human negotiations that can help artificial agents better to resolve conflicts. Problem evolution, a basic aspect of negotiation, can be represented using the restructurable modelling method of developing decision support systems. Restructurable modelling is implemented in the knowledge-based generic decision analysis and simulation system Negoplan. Experiments show that Negoplan can effectively help resolve individual and group conflicts in negotiation.<>

Keywords

cooperative systems; decision support systems; decision theory; human factors; knowledge based systems; problem solving; resource allocation; DSS; conflict resolution; cooperative problem solving; decision support systems; distributed AI; distributed artificial intelligence; group conflicts; human experience; human negotiations; interacting agents; joint decisions; knowledge-based generic decision analysis; problem evolution; resource allocation; restructurable modelling method; sequential decisions; simulation system Negoplan;

fLanguage

English

Publisher

ieee

Conference_Titel

System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on

Conference_Location

Wailea, HI, USA

Print_ISBN

0-8186-5090-7

Type

conf

DOI

10.1109/HICSS.1994.323489

Filename

323489